Mass aconite poisoning from a mislabelled spice product
Bibliographic record
Abstract
INTRODUCTION: (aconite). Most cases of poisoning involve the improper processing of traditional Chinese medicine. We report a mass poisoning event caused by consumption of unprocessed aconite root powders mislabeled as sand ginger. METHODS: We conducted a retrospective case series of patients who presented to two hospitals in the Greater Toronto area with aconite poisoning from a chicken dish eaten at a local restaurant. Demographic, management, and outcome data were collected by review of the electronic medical record. RESULTS: Over an 8 h period, 11 patients presented to hospital with features of aconite poisoning. Symptoms began shortly after ingestion and included perioral paraesthesia (91%) and nausea, vomiting and abdominal pain (64%). In the hospital, the spectrum of illness varied from paraesthesia requiring no intervention (9%) to refractory ventricular dysrhythmias (73%) managed with infusions of sodium bicarbonate, amiodarone, and vasopressors. Two patients received mechanical ventilation for 48 h. No patients died. A public health investigation identified a mislabelled sand ginger spice product imported from China as the source of unprocessed aconite (aconitine 0.55%). DISCUSSION: With the increasing availability of internationally sourced spice products, such events are likely to recur. CONCLUSIONS: This series demonstrates the potential for mass aconite poisoning through contaminated food and highlights the critical role of poison centers and public health systems in responding to such events.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".